#Dataset

Week 14: Which neighbourhoods are the greenest without their parks?Thinking about limited park access to #FlattenTheCurve, we wanted to look at the inequality of greenery throughout the city #TorontoAtlas Wealthy

HumanProgress.org

.@NellFrizzell should read our #SimonAbundanceIndex. Children do not strain the world's resources. In fact, the opposite is true: each new child is correlated with an increase in resource abundance.https://www.humanprogress.org/the-simo

Amir H. Jadidinejad

Most benchmark datasets in the field of RecSys were collected from an existing, already deployed recommendation system (MovieLens, Netflix,…). In this situation, users only provide feedback (r) on the exposed

In the hallowed halls of @PGHtransit headquarters in downtown Pittsburgh, a momentous #opendata event is about to occur. This pumpkin pie represents unpublished transit data currently languishing in the vaults.

Jens von Bergmann

Took a quick peek at the new-ish national dataset on covid case data. In theory it has lots of interesting data, was interested in symptoms. But data fields don't seem

Data acquisition is fun to do, the thrills, the suspense and sometimes the tears. Time to do your analysis and you realize that you have empty spaces in your dataset.Oh

Michael Hoffman

1/Was asked by @jasleen_grewal what I mean by "controls: they're not just for wet lab experiments". Good question!Controls are a principle for analysis of biomedical research data, in general. Not

Denmark short and statisticky wind threadConfronted with 2 presentations of 2018 data.1 from the PF Back summary I noted yesterday ( in https://twitter.com/ScottLuft/status/1198327735455821825)showed wind as 41% of DK's demand.another I

Michael Gensheimer

Let’s talk about measuring performance of predictive models/biomarkers. Can we compare AUC across studies to rank models? Recent machine learning papers have had eye-popping AUC values (such as DeepMind's paper

Oladeji Stephen

RealSaintSteven

Day 12: Dataset In Machine LearningIn #ML, the common task is to study &build algorithms that can learn from and make data predictionsThese algorithms operate by making data-driven predictions by

The European Union makes available on its Open Data portal up-to-date statistics regarding the number of cases and fatalities by country attributed to COVID-19:https://data.europa.eu/euodp/en/data/dataset/covid-19-coronavirus-data/resource/55e8f966-d

Excuse me @shandro. Just wondering why Okotoks, Banff, Canmore, Olds, Black Diamond, Bragg Creek, Camrose, Carstairs, Cremona, Crossfield, Hay Lakes, High River, Mundare, Nanton, Raymond, Penhold and dozens of other

there's a lot of issues with this Tucker Carlson segment, but one claim stuck out to a friend of mine: according to Tucker, 64% of self-classified "liberal" White Americans have

Friday night voyeuring by through logged complaints sent into the city about corona. Best one so far is a woman calling in to narc on her boyfriend going to work

PCA is one of the most famous algorithms for dimensionality reduction and you are very likely to have heard about it in Machine Learning.But have you ever seen it in

Chidiebere Ihemaga

Day 2 of 90Topic: MIN, MAX & AVERAGEIn Excel, it is possible to know from a large dataset the smallest value (minimum or MIN), the largest value (maximum or MAX)